Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Bloomberg business
Speaker 1: Week inside from the reporters and editors who bring you
Speaker 1: America's most trusted business magazine, plus global business, finance and
Speaker 1: tech news. The Bloomberg Business Week Podcast with Carol Messer
Speaker 1: and Tim Stenebeck from Bloomberg Radio.
Speaker 2: Carol Mappler, Tim's done live. You're in San Francisco at
Speaker 2: the Bloomberg Technology Summit, and for to say, Carol, We've
Speaker 2: already heard from the great lineup of speakers. I mentioned
Speaker 2: Flows out of Newman formerly of We Work Lead, a caller,
Speaker 2: the godmother of ai AI. Yeah, Culture Professor heard from
Speaker 2: her a little earlier. Snapsil and Spiegel also here at
Speaker 2: this event. Got a great lineup.
Speaker 3: It's really fun to see the networking going on. We've
Speaker 3: also got our own star and we're talking about Bradstone.
Speaker 4: He is the editor of Bloomberg Business Week. He's also,
Speaker 4: of course the author.
Speaker 3: Of numerous books including those on Amazon, on Amazon, on Bound,
Speaker 3: and so much more. Joining us here at the Bloomberg
Speaker 3: Tech sum and actually you have invited us in, so
Speaker 3: thank you so much for that. First of all, I
Speaker 3: feel like there's so much going on AI. Yes, but
Speaker 3: tell us about Brad. The conversations you guys had as
Speaker 3: a team about what you wanted to cover there.
Speaker 5: Yeah, you know, it's funny.
Speaker 6: We do these every year and we tried not to
Speaker 6: repeat ourselves, and last year we were really talking about
Speaker 6: the emergence of chat GPT. It had gotten everybody talking,
Speaker 6: and so of course we had Sam Altman as our
Speaker 6: keynote speaker, and you can't buy the same people every year.
Speaker 6: But the other thing that's happened is it has started
Speaker 6: a movement, and so we thought, well, who else do
Speaker 6: we want?
Speaker 5: And the first names that's sprung to mind.
Speaker 6: Are the founders of Anthropic Siblings.
Speaker 5: Dario and Daniela Amoday.
Speaker 6: They actually worked at the Open AI and spun out
Speaker 6: maybe with an implicit objection to how open A was
Speaker 6: being run. That's where we started today and it's really
Speaker 6: set the tone for the conversations today mentioned faife A Lee,
Speaker 6: We have been coaches, la Reid Hoffmann coming later. Really,
Speaker 6: I think where we settled on was like, let's find
Speaker 6: some of the architects of this moment and to ask
Speaker 6: them the hard questions about are we really kind of
Speaker 6: comfortable where we're going?
Speaker 5: Or is this an arms race that is propelling everyone
Speaker 5: forward just to win?
Speaker 2: And what does that mean? So what does that mean?
Speaker 2: Because you know, if we think about where we were
Speaker 2: a year ago when everybody was playing with chat GPT.
Speaker 2: GPT four had basically just come out a little over
Speaker 2: a year ago, when you had the Tech summit, here,
Speaker 2: where are we this year with the run up in video?
Speaker 2: You have Amazon investing in anthrophic, you have all the
Speaker 2: open high eigh drama that happened at the end of
Speaker 2: last year. Where are we when it comes to sort
Speaker 2: of like AI being in primetime this Yes.
Speaker 5: I will answer with something that you will never hear
Speaker 5: on the stage downstairs.
Speaker 2: Okay, I don't know here and an.
Speaker 6: Age of remarkable what I call AI ambiguity. There's so
Speaker 6: many things we don't know. So for example, Meta has
Speaker 6: open source the Lamaitrie model. What does that mean for
Speaker 6: these other companies that have spent hundreds of millions maybe
Speaker 6: seeing billions to train and operate a model. What does
Speaker 6: it mean that you can now get the technology for free?
Speaker 5: Will chatbots be a thing that we regularly use or are.
Speaker 6: They a novel expression of the technology and then they'll
Speaker 6: fade away?
Speaker 5: Are their lanes for startups outside.
Speaker 6: Of what all the big tech companies that have the
Speaker 6: resources are doing with AI.
Speaker 7: These are great questions. I actually don't think that anybody.
Speaker 5: Has the answer.
Speaker 6: I think that even when I think about social media
Speaker 6: explosion or on demand apps fueled by the iPhone, that.
Speaker 5: We sort of had a sense of where, Okay, well
Speaker 5: this is cool and people will.
Speaker 2: Find it useful.
Speaker 6: And I just think everything from how will use it
Speaker 6: to what the economics will look like are still completely
Speaker 6: up in the air.
Speaker 3: I love that you went there, because I do feel
Speaker 3: like we've all been agog if you will, right on Nvidia.
Speaker 4: And the chips and so and so forth coming off
Speaker 4: of milk, and I just came and people.
Speaker 3: To even are like trying to assess where do we
Speaker 3: put allocate the money going forward? So much of what
Speaker 3: I heard rod was data centers right and infrastructure build out.
Speaker 3: Like people were still like, we haven't quite figured out
Speaker 3: the applications.
Speaker 4: Of AI going forward.
Speaker 5: I think that's true.
Speaker 6: Where where I'm sort of bullish and why don't you
Speaker 6: let's see us an example of the good old Bloomberg terminal,
Speaker 6: where you really need to know how to get information
Speaker 6: from the terminal, right, we know a whole lexicon and
Speaker 6: that's pretty similar to other computer systems. They they'll do
Speaker 6: what you tell them to do, and often you need
Speaker 6: to speak a particular language, maybe even coding.
Speaker 7: And what AI is.
Speaker 6: I think of it as like a new user interface
Speaker 6: where you can express yourself either with a voice command
Speaker 6: or a written command and a plain language and have
Speaker 6: it respond.
Speaker 2: And have it do things for you.
Speaker 6: I think that is like and I said, we're going
Speaker 6: to see an IO next week with Google and WWWC, WWDC,
Speaker 6: with Apple them baking it into their devices and basically
Speaker 6: creating a new way to use technology.
Speaker 2: Is it too early to say, Brad, that we're in
Speaker 2: an era right now like we were with the web
Speaker 2: browser in the nineties, sort of the dawn of the Internet,
Speaker 2: you know, tech bubble. Notwithstanding, but the idea that there
Speaker 2: was this new technology that fundamentally changed not just the
Speaker 2: way we live, but the way we interact with each
Speaker 2: other and the way that we spend money.
Speaker 6: I'm going to go back to my handy AI ambiguity.
Speaker 7: And say, I don't know.
Speaker 5: I mean, if if this is the.
Speaker 6: Domain of only the biggest companies that can afford it,
Speaker 6: and their proxies like Anthropic that maybe it isn't a
Speaker 6: giant ce that lists all boats.
Speaker 5: Maybe you know, this is going to be.
Speaker 6: Owned by four or five companies and governments around the world,
Speaker 6: and it will concentrate their power. The arrival of the
Speaker 6: web browser was the arrival of all sorts of entrepreneurial opportunity.
Speaker 6: To point, you know, we had a rise and then
Speaker 6: a crash, and then a rise again. I don't think
Speaker 6: it's clear that this is ready set go for everyone.
Speaker 6: It's very expensive to run these models. They'll maybe regulated,
Speaker 6: as fafe Lea said earlier today. If you regulate them,
Speaker 6: you could create a powerful black market based on open
Speaker 6: source models.
Speaker 5: So all sorts of sort of unresolved issues. And I'm
Speaker 5: just not sure.
Speaker 6: Despite the fact that you go to y Combinator, any
Speaker 6: startup community here and all you will see and hear
Speaker 6: about are AI startups.
Speaker 5: I'm just not sure how big the opportunity is going
Speaker 5: to be.
Speaker 2: We'll see.
Speaker 3: Hey, Adam Newman, you know you think about cycles right
Speaker 3: in technology, and we're trying to still figure out right
Speaker 3: the AI cycle going forward. But how what did you
Speaker 3: want to know or what you know, Adam Newman in
Speaker 3: terms of you think about we were what how it
Speaker 3: was a cover of Bloomberg.
Speaker 4: Business Week, maybe.
Speaker 3: Several times I can't remember before Brad's time, before Brad's time,
Speaker 3: but nonetheless it was a great story.
Speaker 4: We talked so much about that company and where it
Speaker 4: was going, and obviously it's gone through.
Speaker 7: Well.
Speaker 6: First of all, I felt so privileged to be able
Speaker 6: to bring his particular brand of charismatic lunacy.
Speaker 5: Uh oh, you know that's I don't mean.
Speaker 6: In a harsh way. You know, he's entertaining as heck. Yeah,
Speaker 6: like he exudes charisma. He's at it again.
Speaker 5: I wanted.
Speaker 6: He's trying to buy where you work out of bankruptcy.
Speaker 6: So that was the first topic. He he they've they've
Speaker 6: not taken his bid, and he's clearly signaling that he's
Speaker 6: going to appeal that they don't. They think that the
Speaker 6: creditors should have looked at his bid more carefully, that
Speaker 6: he had the higher bid. He said that the current
Speaker 6: creditors who won the deal are making promises they can't keep.
Speaker 6: So that was the first topic. Then we asked him
Speaker 6: up flow his residential real estate company.
Speaker 7: You know, this idea of.
Speaker 6: Spending hundreds of millions of dollars to acquire properties and
Speaker 6: then not just be a landlord, but to use technology
Speaker 6: to create community and a sense of belonging. Him bringing
Speaker 6: his classic sense of uh, you know, quasi mysticism into
Speaker 6: the world of business.
Speaker 5: And I asked, I was like, why do you keep
Speaker 5: we were, Yeah, why do you have that?
Speaker 8: You know?
Speaker 5: But it's who he is and he you know, he's.
Speaker 6: Somebody who speaks to the heart. I asked him a
Speaker 6: little bit. I wanted to know about whether he was different,
Speaker 6: and I really didn't do get the sense of one,
Speaker 6: he's got a confrontational board now that's gonna say no
Speaker 6: to him.
Speaker 5: He didn't have that before.
Speaker 4: And that too, he's there's an adult, a couple of
Speaker 4: adults in the glorio.
Speaker 5: There were before, but they weren't acting like it.
Speaker 6: And that he even said that on his latest proposal.
Speaker 6: Mark Andresam told him no, Yeah, that's interesting. I'm not
Speaker 6: sure Masayoshi Son ever told him no. And then the
Speaker 6: third thing was I wanted to know from him how
Speaker 6: he was different as a CEO. And he mentioned the board,
Speaker 6: and he also mentioned the advice that Jeff Bezos had
Speaker 6: given him to always talk last in a meeting because
Speaker 6: otherwise you're gonna kind of pollute the water and sway
Speaker 6: people's opinion.
Speaker 5: And I said, are you able to follow that advice
Speaker 5: to go well?
Speaker 6: And his CFO was sitting in the audience and gave
Speaker 6: us a kind of half hearted thumbs up.
Speaker 5: So maybe something to work on.
Speaker 2: So do you see him pulling off that we work
Speaker 2: out of bankruptcy.
Speaker 5: I don't know if he will win that deal. I
Speaker 5: think that.
Speaker 6: You know, the creditors are are required and it is
Speaker 6: in their personal interest to get the most money for
Speaker 6: the death that exists and to bring the company out
Speaker 6: of the bankruptcy. And the fact that they've chosen this
Speaker 6: other path suggests to me, and I haven't really looked
Speaker 6: at it, but that it may be a more complicated
Speaker 6: picture that Adam has presented and that it may not
Speaker 6: only be about a popularity contest. And I also asked
Speaker 6: him to explain to me why we work should be
Speaker 6: in flow and whether it was just a personal mission
Speaker 6: of redemption.
Speaker 5: And I wasn't sure.
Speaker 6: I really believe, you know, fully believed that those two
Speaker 6: companies belong together and that it wasn't a little emotional
Speaker 6: for him.
Speaker 5: In fact, he said that it.
Speaker 8: Was so.
Speaker 6: You know, and maybe there are personal reasons the quest
Speaker 6: that they don't want to resell we work to Adam Newman.
Speaker 5: We can all imagine what they are. He wasn't you know?
Speaker 6: He the company had problems under his leadership, and the
Speaker 6: question is are those personal reasons do they meet a
Speaker 6: valid legal test?
Speaker 3: You know, it's fascinating think about the pandemic and how
Speaker 3: we're rethinking how we work and what kind of office space.
Speaker 4: Is ultimately needed.
Speaker 3: Like his thinking about this concept of having flexible workspace
Speaker 3: like as you need.
Speaker 4: It wasn't so far fetched. It's just timing and maybe execution.
Speaker 6: And I mean I would say this, I think that
Speaker 6: the history of real estate is and you know, Donald
Speaker 6: Trump has exhibit A is a is a history of
Speaker 6: ups and downs, bubbles and crashes.
Speaker 5: We're seeing in China right now.
Speaker 6: Business Week we did a list of all the billionaires
Speaker 6: that have lost everything betting on the Chinese.
Speaker 5: So that's no different.
Speaker 6: But you know the difference is he voted a little higher,
Speaker 6: wrapped in a mantle of being a technology company and
Speaker 6: trying to take a public as a tech company, and
Speaker 6: then wrote it even lower because investors ultimately.
Speaker 2: Didn't buy the visual.
Speaker 4: Can I talk about.
Speaker 7: Robot?
Speaker 6: Yes, this is a humanoid robot developed by Engineered Arts,
Speaker 6: a company in Cornwall, England. I'm about to go in
Speaker 6: a either a career high or a career low. I'm
Speaker 6: going to go on stage and interview the robot.
Speaker 2: So it's going to answer your questions in real time.
Speaker 6: Yes, yeah, yeah, it's a creepily human like It speaks
Speaker 6: and I presume should be addressed as a female.
Speaker 7: That's a choice.
Speaker 5: That's a choice, and it's really remarkably I wouldn't say it's.
Speaker 7: Lifelike, but because I did address it, I did some tests.
Speaker 6: It's expressive and it's design to make people feel comfortable
Speaker 6: with it. It's very it's to me, even though it's
Speaker 6: a British project, it very much reminds me of the
Speaker 6: Japanese bipedal robots or the past that Sony and Samsung
Speaker 6: and they were always working on them. The Japanese love
Speaker 6: their their bipedal robots.
Speaker 2: It's certainly like it's it's incredible novelty. But we should
Speaker 2: know that there are lots of companies working on robots
Speaker 2: like this to help in warehouses. Think about what it
Speaker 2: would you do a company like Amazon to be able
Speaker 2: to have you.
Speaker 7: Know, this am a coon.
Speaker 6: I hope at least does not move because if you
Speaker 6: see me running across the stam, I don't know, uh
Speaker 6: that it's an ambulatory Uh yeah, now I could ask
Speaker 6: and it's running chat GPT for Turbo.
Speaker 9: So I think that's.
Speaker 2: Interesting that, So explain what that means.
Speaker 6: Like it's essentially that engineered arts has developed the machine,
Speaker 6: but the brains are borrowed using the API of open.
Speaker 5: AI and chat GPT.
Speaker 6: Well that's interesting going forward that maybe robot makers don't
Speaker 6: need to worry as much about main general intelligence, but
Speaker 6: they get hooked into one of these large models, use
Speaker 6: the API, and they can they can be more engineering
Speaker 6: companies that think about things like how the joints work,
Speaker 6: how balance works, as you mentioned Caro, all the expressiveness
Speaker 6: of the robots.
Speaker 2: So what does that mean she's note connected to the
Speaker 2: cloud right now?
Speaker 7: Oh?
Speaker 5: I would imagine that she is. Okay, yeah, well we'll
Speaker 5: see if Wi fi goes down.
Speaker 2: Answer to make sure she's on the right network. Okay,
Speaker 2: I was thinking and I were talking.
Speaker 4: About the hotel. We're saying we're not gonna say where
Speaker 4: it is, but.
Speaker 3: It's like, right, we couldn't get anybody I answer, So
Speaker 3: we could have used Amica to like answer our phone
Speaker 3: call and like help us answer some question.
Speaker 2: There is the conference, which is like huge, Well that's
Speaker 2: the thing.
Speaker 7: It's like you would need Amica to do that.
Speaker 6: You would need an Alexa or chatch BT, right, and
Speaker 6: then and then robots can just be these physical things.
Speaker 6: And and the question is do we really need a
Speaker 6: buy pedal robot that's trying to trick us into being
Speaker 6: thinking that it's human or will they be Timmy mentioned
Speaker 6: industrial robots, you know, little things that do very specific tasks,
Speaker 6: deliver the mail, deliver packages, that kind of thing.
Speaker 3: Hey, can I ask you what's the biggest I don't know,
Speaker 3: I know AI like as you go through today, like
Speaker 3: what are you looking for a question to be answered?
Speaker 3: Or something like I think you know so much this world,
Speaker 3: there's something top of.
Speaker 7: Mind for you.
Speaker 5: I mean, I think we all want to know, like
Speaker 5: where it's going. I guess specifically, we've seen it.
Speaker 6: Since the September of twenty twenty two, every successive models
Speaker 6: of chat GBT or any of these other.
Speaker 5: Chatbots has been step change improvements.
Speaker 6: Fed by more and more data and more and more
Speaker 6: processing and power and money running on in video chips.
Speaker 5: So my question is is that going to continue or are.
Speaker 6: We hitting a natural limit, either in the money that
Speaker 6: we could spend, the train, the available processors, or or
Speaker 6: just the model matches out all right and it's not
Speaker 6: giving us step change improvements anymore.
Speaker 4: Good stuff from Bradstone.
Speaker 3: As always, We've got more, including we're to continue with AI.
Speaker 2: Folks, this is Bloomberg.
Speaker 1: You're listening to the Bloomberg Business Week podcast. Catch us
Speaker 1: Live weekday afternoons from two to five pm Eastern Listen
Speaker 1: on Apple.
Speaker 2: Car Play and then Broyt Auto with.
Speaker 1: A Bloomberg Business act or want us live on YouTube?
Speaker 2: Still give value? No question buzzing about AI. We've been
Speaker 2: talking about it. But venture capital dealmaking, Carol, it's still suppressed.
Speaker 2: I got some stats here. Here's some numbers. Okay here
Speaker 2: in the US VC's thirty six point six billion into
Speaker 2: startups in the first quarter of the year. That's according
Speaker 2: to Pitchbook. The funding went to twenty eight hundred companies.
Speaker 2: On both measures, it's a nearly thirty percent decrease compared
Speaker 2: with the same period in twenty twenty throws three. So
Speaker 2: the takeaways startups had their worst funding your last year
Speaker 2: since twenty nineteen. This year it's starting off even worse.
Speaker 3: So despite of the excitement, Well, we've got a great
Speaker 3: boys to really talk to us about the startup community.
Speaker 4: Alien Lee is with us.
Speaker 3: She's the founder and managing partner of the VC firm
Speaker 3: Cowboy Ventures. They invest mostly in software companies based here
Speaker 3: in the US. We should say that her firm has
Speaker 3: made more than one hundred early stage investments, specializing in
Speaker 3: seed rounds.
Speaker 4: She's on site with us. The other thing is she
Speaker 4: has done the data analysis.
Speaker 3: That is the reason we use the word unicorn when
Speaker 3: it comes to startups.
Speaker 4: We love data here at Bloomberg.
Speaker 5: How are you.
Speaker 4: I am so happy to be here. We'll tell us
Speaker 4: about the VC world, Like give us an idea. It's
Speaker 4: a great indicator in terms of the health of the economy.
Speaker 8: So we just finished a panel myself, Kirsten Green and
Speaker 8: auDA from Base ten with Tom Giles, who's the tech
Speaker 8: editor for Bloomberg Tech I.
Speaker 4: We talked about what's going on.
Speaker 8: So, like you mentioned, we had a big slowdown last year.
Speaker 8: A lot of people put their pencils down. They're both
Speaker 8: like it felt like there was a falling night in
Speaker 8: terms of public markets, which obviously affects the private markets,
Speaker 8: and so people said it's not a great time to
Speaker 8: be investing in private companies.
Speaker 4: I do think that we're.
Speaker 8: Seeing quite a pick up this year, but it's largely
Speaker 8: driven by AI, which is great. It's very exciting. It
Speaker 8: is the new hotness in venture capital. So you just
Speaker 8: have to It can be quite treacherous, I think to
Speaker 8: invest in AI right now because it's you know, obviously
Speaker 8: there's a lot of energy right now. We're kind of
Speaker 8: in a consolidation phase, and for very good reasons, right
Speaker 8: with whether it's Microsoft or Meta or Salesforce or Service.
Speaker 7: Now or Google.
Speaker 8: You need a lot of open AI, you need a
Speaker 8: lot of money, you need a lot of GPU, you
Speaker 8: need a lot of engineers, and so there's kind of
Speaker 8: this like techtonic plate war going on in the big
Speaker 8: tech players right now, and so if you've got a
Speaker 8: really big fund, you could try and align your Obviously,
Speaker 8: most of these companies are public companies right so right
Speaker 8: it's a great time for public Nvidia and to be
Speaker 8: a public markets investor to be able to get exposure
Speaker 8: to like the AI that is going to be powering.
Speaker 8: I think most applications for decades to come. But for
Speaker 8: private markets, I think there's just a lot of money
Speaker 8: going into startups, many of whom are.
Speaker 5: Not going to make it.
Speaker 2: So the thing that's interesting about this, and Brad kind
Speaker 2: of alluded to him, we were talking to him, is
Speaker 2: the idea of it's so expensive to have this processing
Speaker 2: power to buy these GPOs. Yeah, and it's not as
Speaker 2: easy as you know, ten fifteen years ago creating an
Speaker 2: app yeah, and building a network, yeah, which was sort
Speaker 2: of what we saw venture capital support in that generation.
Speaker 7: Yeah.
Speaker 9: Is there a concern that you.
Speaker 2: Know, you do early stages, yeah investing, you do seed startups,
Speaker 2: your seed investing. Is there a concern that these companies
Speaker 2: just can't raise the capitol in order to subsport them.
Speaker 8: So there are large models that the big technology companies
Speaker 8: are investing in that have billions of parameters that you
Speaker 8: need billions of dollars for GPOs. We have been investing
Speaker 8: at Cowboy Ventures, as you mentioned, we're seed stage investors.
Speaker 8: Our first AI driven enterprise software companies we invested in
Speaker 8: eight years ago, where it's they use what we call
Speaker 8: small model where they don't need.
Speaker 4: To buy GPUs.
Speaker 8: They basically get a proprietary data set. In that case,
Speaker 8: the company's called text You, and we basically got HR
Speaker 8: related documents, jobs, pecs, performance reviews, and we train the
Speaker 8: AI using very situational specific parameters to basically understand how
Speaker 8: it can help people write performance reviews more effectively, how
Speaker 8: it can help people write job specs more effectively. And
Speaker 8: you just don't need the giant GPU to be able
Speaker 8: to do that work. And then also a lot of
Speaker 8: it is around how you solve the problem for everyday
Speaker 8: business users instead of them using Google Docs or word
Speaker 8: you need to figure out how would I get into
Speaker 8: their workflow, whether it's through workday or lattice, and how
Speaker 8: do I actually create those integrations so that the way
Speaker 8: that the AI can be in the business process of
Speaker 8: every day people inside the enterprise. And so I think
Speaker 8: that's those kinds of business or industry specific applications.
Speaker 4: You don't need billions of dollars to build those applications.
Speaker 4: But is that scalable Okay, I'm listening to you. Is
Speaker 4: that scalable elsewhere elsewhere? Meaning other industries like that mod completely.
Speaker 8: So we're seeing I think a lot of what's the
Speaker 8: app there's the application layer and there's infrastructure, right, so
Speaker 8: there's money going into both at the application layer.
Speaker 4: That's where a lot of VC funds are playing right now.
Speaker 8: And it makes a lot of sense because so many
Speaker 8: people in whether it's the food and beverage industry, in hospitals,
Speaker 8: in education, people are still using pen paper spreadsheets. They're
Speaker 8: not actually leveraging the underlying data, and the applications that
Speaker 8: use every day are not smart. And so I think
Speaker 8: there's pretty much every industry and every application that we
Speaker 8: look at today is going to have new applications that
Speaker 8: are powered by AI.
Speaker 4: So it is a tremendous opportunity.
Speaker 2: Okay, I'm speaking of opportunities. I'm wondering what's more difficult
Speaker 2: in this world where cash can earn four and a
Speaker 2: half to five per tails. That's an opportunity. Yeah, what's
Speaker 2: harder right now?
Speaker 10: Now?
Speaker 2: Is it harder to go raise money from investors to
Speaker 2: then deploy yeah, or is it harder to find the
Speaker 2: companies to deploy that money into.
Speaker 8: We're very fortunate, you know, we're pretty disciplined. Fun We've
Speaker 8: been around for over ten years now. We've had pretty
Speaker 8: much the same investors or what we call LP Limited
Speaker 8: Partners for pretty much the ten years, so we're very
Speaker 8: fortunate and they are savvy investors who understand the upside
Speaker 8: of investing in venture capital firms and they know it's
Speaker 8: a ten to fifteen year investment. So fortunately for us,
Speaker 8: it's definitely gotten harder, and it's I think in many
Speaker 8: ways it's good because it holds us very accountable. It's
Speaker 8: like there are benchmarks that you have to beat to
Speaker 8: be worth investing in, and that's our job is to
Speaker 8: make sure that we beat those benchmarks fund after fun
Speaker 8: and also we raise every three years or every four years,
Speaker 8: so you know, you raise the fund and then you
Speaker 8: have three years to basically go find some great investments.
Speaker 8: So that's the it's gotten quite competitive in private markets.
Speaker 8: A ton of money flooded in in twenty twenty, twenty
Speaker 8: twenty one, and it's probably not going to it's not
Speaker 8: going to recede, and so there's just more money chase
Speaker 8: saying private companies than ever.
Speaker 3: One thing I wanted to ask you, Aleen, is what's
Speaker 3: with all the attention on AI where what's being neglected
Speaker 3: maybe in the venture world or where do you think
Speaker 3: we should also be thinking about when it comes to
Speaker 3: tech innovation.
Speaker 4: I mean, I do think, oh, that's a really good question.
Speaker 4: I think the big boom when interest.
Speaker 8: Rates were basically zero in twenty twenty and twenty twenty one,
Speaker 8: it brought so much attention to the venture capital and
Speaker 8: technology world that actually what we would have considered long
Speaker 8: tail markets parking garages, like companies selling software to parking garages.
Speaker 4: Got funded.
Speaker 8: Like the Unicorn analysis that we did in twenty thirteen
Speaker 8: versus twenty twenty three showed a huge difference in the
Speaker 8: amount of money that's going to industry specific software whether
Speaker 8: and so in the original Unicorn analysis in twenty thirteen,
Speaker 8: it was actually, it's quite interesting how it flip flopped
Speaker 8: eighty percent consumer companies and twenty percent enterprise software companies.
Speaker 8: Ten years later it foot flopped and became eighty percent
Speaker 8: enterprise twenty percent consumer. And so in those enterprise you've
Speaker 8: got climate tech companies, you've got agriculture companies, you've got
Speaker 8: companies serving parking garages. So entrepreneurs especially, I think since
Speaker 8: the iPhone debuted in two thousand and seven, pretty much
Speaker 8: everyone in the modern world understands the power of technology,
Speaker 8: and so if they work in a coord if they
Speaker 8: work in at a nursing station, they understand how much
Speaker 8: inefficiency there is and how much opportunity there is for
Speaker 8: technology to actually reinvent the way they do things and
Speaker 8: let humans.
Speaker 4: Do what they do best better. Waiting for health care
Speaker 4: to really embrace.
Speaker 2: Technology, keep waiting. You know, if you need give you a.
Speaker 4: Chip information, I'm ready to do that.
Speaker 2: I actually am. If you need a copy of the
Speaker 2: X ray, here's a CD ROW. I'm not joking. Earlier today,
Speaker 2: that's still the way like ten back then.
Speaker 8: Ode posts Let's speak earlier today with Emily Chang, and
Speaker 8: he was saying that the thing that he's going to
Speaker 8: tell President Biden tomorrow is that every person should have
Speaker 8: a personal doctor and every case to have a personal
Speaker 8: tudor tutor, and that that would reinvent both education and
Speaker 8: lighters and it.
Speaker 4: Would be amazing.
Speaker 1: You're listening to the Bloomberg Business Week podcast. Listen live
Speaker 1: each weekday starting at two pm Eastern on Apple car
Speaker 1: Play and Android Auto with the Bloomberg Business Ad. You
Speaker 1: can also listen live on Amazon Alexa from our flagship
Speaker 1: New York station, Just Say Alexa, playing Bloomberg eleven thirty.
Speaker 2: Well Tick Ventures is a free seed and seed venture
Speaker 2: capital firm. It focuses on investing in demographic changes that
Speaker 2: are driven by tomorrow's Internet users. So what that means
Speaker 2: as far as where they put their money. There's a
Speaker 2: company out there called Raars where you can invest in
Speaker 2: sneakers and collectibles. Right. It's an aipowered workforce training platform,
Speaker 2: and then it comes to be behavioral health. The platform
Speaker 2: is called it most days. That's among other investments ADMD.
Speaker 4: I love the idea of demographics.
Speaker 3: I really think it's kind of figure out what are
Speaker 3: the trends not only today but really more importantly up
Speaker 3: tomorrow with us right now is Monique Woodward. She's founding
Speaker 3: partner managing partner at Cake Vners. Welcome, Welcome, so nice
Speaker 3: to be talking with you.
Speaker 4: Thank you, thanks for having me.
Speaker 3: When you think about demographics, right, so you can dice
Speaker 3: and slice that, we make so many different ways. What
Speaker 3: are the demographics that you really like to focus on
Speaker 3: in today's environment?
Speaker 11: So the Cake Venture's thesis around demographics is really based
Speaker 11: on a few different layers. The first layer is aging
Speaker 11: and longevity. There's ten thousand people turning sixty five every
Speaker 11: single day in this country alone. And there's this massive
Speaker 11: opportunity to help them use technology to make their lives
Speaker 11: better as a age. The second layer of the cake
Speaker 11: is the increased spending power of women and how the
Speaker 11: female dollar drives companies to billion dollar plus outcomes. And
Speaker 11: then the third is the shift to majority minority, where
Speaker 11: people of color as a broad group, primarily Latino, Asian
Speaker 11: and Black, becoming majority in the United States, are already
Speaker 11: a global majority.
Speaker 4: You know, it's really fascinating. I keep talking about this.
Speaker 4: I was just back from Milkin and I had to
Speaker 4: moderate a panel. It was called Thriving in Distruction.
Speaker 2: Oh, you did several panels, but what was.
Speaker 4: Interesting on our pref call.
Speaker 3: So here I have somebody from real estate, from venture,
Speaker 3: private equity guide, private credit guide, somebody who's in, you know,
Speaker 3: trading every day on a platform over at Citadel Securities,
Speaker 3: and what they wanted to talk about was longevity and
Speaker 3: the aspect of how it's going to impact things like
Speaker 3: pension app obligations, how we live, the kind of housing
Speaker 3: we need, you know, whether we bring older people back
Speaker 3: into the workforce.
Speaker 4: What are the important.
Speaker 3: Conversations that you think we need to be thinking about
Speaker 3: when it comes to longevity and how that shapes specifically
Speaker 3: your investments.
Speaker 11: I think the big conversation right now is around how
Speaker 11: do we live longer?
Speaker 3: Right?
Speaker 4: But I think that's just touching the surface of longevity.
Speaker 4: It's really about how do we use.
Speaker 11: Technology to give people better lives at older ages as
Speaker 11: they get older, right, how do we use technology to
Speaker 11: enhance their lives, help them age in place without moving
Speaker 11: into a nursing home or retirement home, And how do
Speaker 11: we give them better lies after sixty as they had
Speaker 11: when they were in their twenties and thirties.
Speaker 2: I'm wondering about the third theme that you touched on
Speaker 2: in terms of demographics, the idea of investments in companies
Speaker 2: that are not necessarily geared toward people of color. But
Speaker 2: take this demographic into account. Here we are in Silicon Valley,
Speaker 2: not necessarily the most diverse place when it comes to
Speaker 2: where venture capital is deployed. I think that's fair to say,
Speaker 2: how do you think about that in terms of where
Speaker 2: you're putting your money in terms of the opportunities that
Speaker 2: are out there? Because I think a big criticism that
Speaker 2: folks have about ventor capitalist is, you know, they're always
Speaker 2: just trying to solve problems that they have, Like, you know,
Speaker 2: it's true, how do we get to tahoe faster? Right
Speaker 2: to get to get a skew day out. I'm not
Speaker 2: trying to be dismissive, but I mean it's like, you know,
Speaker 2: it's like common criticism.
Speaker 11: So one of the categories that I do a lot
Speaker 11: of investing in it is the future of deskless work.
Speaker 11: Eighty percent of the labor market is actually deskless work,
Speaker 11: non office work, work that doesn't happen in an office,
Speaker 11: health care jobs, construction jobs, service worker jobs. As you
Speaker 11: might expect, a lot of these jobs over index in
Speaker 11: women and people of color, and so I think that
Speaker 11: AI and new technologies are going to be really important
Speaker 11: in accelerating the adoption of those jobs, but also accelerating
Speaker 11: the efficiency of those jobs. And so I think we're
Speaker 11: at this really important inflection point where we can use
Speaker 11: technology to improve the lives of healthcare workers, improve the
Speaker 11: lives of service workers, and we haven't been doing it
Speaker 11: because to your point, a lot of the people who
Speaker 11: have been building for building technology that they come from
Speaker 11: a knowledge worker background. So their immediate thought is to
Speaker 11: build future work products software for knowledge workers. But these
Speaker 11: massive opportunities have happen in healthcare and construction and manufacturing,
Speaker 11: and those jobs are often held by.
Speaker 7: People of color.
Speaker 3: You know, I'm watching Bradstone up on stage with Amaica
Speaker 3: the robot, and I'm thinking about in terms of how
Speaker 3: care like whether or not there is some way.
Speaker 4: I mean, one of the other trends that came.
Speaker 3: Out of Milkan is that this shortage of health care
Speaker 3: workers in particular, and I do wonder is there some
Speaker 3: way in technology innovation that we can assist.
Speaker 4: Those folks who actually have to do things.
Speaker 3: In care for people, or whether because we're facing shortages
Speaker 3: in a big way in that industry.
Speaker 11: Well, we're already seeing it in companies like a Bridge,
Speaker 11: a Bridge which raises series C in order to use
Speaker 11: conversational as the conversations between healthcare workers and their patients.
Speaker 4: And convert them into usable data.
Speaker 11: So we're already seeing AI being really useful in the
Speaker 11: lives of healthcare workers.
Speaker 8: Right.
Speaker 11: I'm very skeptical about the use of robotics in actual
Speaker 11: patient to patient to healthcare worker interactions, but I do
Speaker 11: think that AI is useful in freeing up the job
Speaker 11: of the healthcare worker in order to make those patient
Speaker 11: interactions much more robust, much more have a lot more depth.
Speaker 11: And so I think we're far away from robots doing
Speaker 11: that job, but I think we're we're in the AI
Speaker 11: doing it.
Speaker 2: I guess also maybe cut down on error too. When
Speaker 2: you're tasked to a doctor. I mean, this is something
Speaker 2: I recently noticed. When you're trying to describe like a
Speaker 2: pain that you're having to a doctor, some sort of symptoms.
Speaker 2: I mean, they're essentially serving the function of AI. What
Speaker 2: they're doing is, you know, they're saying, Okay, well you
Speaker 2: have this, this and this, here's your family history. They're
Speaker 2: taking all these data points and they're trying to diagnose
Speaker 2: you with something that you have. It's so easy to
Speaker 2: see how that could be better served by something in
Speaker 2: the cloud.
Speaker 11: Exactly, or at least augmented in some way augmented. I
Speaker 11: think that's what I think that's what we're looking for
Speaker 11: within healthcare in particular. We are looking for technology to
Speaker 11: augment the already great skills that these nurses, nurse practitioners,
Speaker 11: and doctors already have.
Speaker 4: We're not looking to replace them with robots, but give.
Speaker 11: Them additional tools that make their jobs more efficient and
Speaker 11: allow them to spend more about one on one time
Speaker 11: with patients.
Speaker 4: That's whole idea have adjacent right in terms of AI, Nick,
Speaker 4: thank you so much. We really appreciate you coming by.
Speaker 4: Thank you so much, fatterning time with our audience.
Speaker 3: It's a lot of Nick Woodward g She is founding
Speaker 3: partner and managing partner at Cake Ventures, joining us here
Speaker 3: at the Bloomber of Technology Summit.
Speaker 4: But these are some of the discussions and technologies like figuring.
Speaker 3: Out what does it mean for our workplace? I mean,
Speaker 3: you and I kind of joke about a kid about it.
Speaker 3: But if we could get an assistant kind of writing
Speaker 3: our scripts.
Speaker 4: On otaily basis, I wouldn't mind that.
Speaker 2: I was thinking about that a lot yesterday. I didn't
Speaker 2: get when I was working. But to be fair, I mean,
Speaker 2: you were literally, you know, ten hours of sleep in
Speaker 2: the past four days because of what you were doing.
Speaker 2: But the truth day is, there are a lot of
Speaker 2: repetitive tasks out there. It would be great to see
Speaker 2: some of those be replaced by machines of people. Look,
Speaker 2: I oftentimes think about this conversation in the context of
Speaker 2: other big historical shifts when it comes to the types
Speaker 2: of work that people did one hundred years ago versus
Speaker 2: the type of work we're doing now. Right, we don't
Speaker 2: need a horse and buggy to get us from place
Speaker 2: to place, you know. So what was replaced, you know?
Speaker 2: And what did that allow people to do? What did
Speaker 2: the steam engine allow people to do?
Speaker 8: It?
Speaker 2: Just does this thing stick the way that you know.
Speaker 7: The proponents of it?
Speaker 3: Even to go back that for I think about when
Speaker 3: I started out in journalism, when I needed research, I
Speaker 3: mean was on the phone with folks in the government,
Speaker 3: like Commerce Department, can you FedEx overnight or send me research?
Speaker 2: Really for my reports, like not emailing it to you.
Speaker 3: It's amazing the stuff that I used to get in
Speaker 3: the email And now I just go on the Internet
Speaker 3: and I.
Speaker 4: Just pull it right up.
Speaker 3: So you just think about that transition. It's made my
Speaker 3: job a lot easier. And I do feel like that
Speaker 3: access to information is freeing.
Speaker 4: How infladible that is.
Speaker 3: That's something Elon talked about. He was talking up Starling,
Speaker 3: but he said that's the great leveler in terms of
Speaker 3: creating Internet access to everybody around the world. That means
Speaker 3: everybody can get an education. M I tam cimate forces online.
Speaker 4: Like you think about things like that.
Speaker 3: But I feel like with this next Lettle level of AI,
Speaker 3: I'm not quite so sure about it could be pretty cool.
Speaker 2: Those are the good things that that's good, you know,
Speaker 2: we think and that's what that was the promise of
Speaker 2: the Internet. But look at the Internet's also been used
Speaker 2: for a lot of really bad stuff. I mean, we
Speaker 2: had the cover of Bloomberg business Week recently talk about
Speaker 2: the way that social media platforms are becoming places where
Speaker 2: teenage boys essentially have been held hostage and it's led
Speaker 2: to some really discribbing outcomes. All right, again all as
Speaker 2: a result of the Internet.
Speaker 3: All right, So on two sides to every coin. And
Speaker 3: this is what we want to get into because I'm
Speaker 3: here at the Bloodberg Technology Summit. There's a workshop going on.
Speaker 3: It's called addressing AI Risks in Business, and we have
Speaker 3: a great voice to.
Speaker 4: Talk to us about that.
Speaker 5: Anthony A.
Speaker 4: Giri is executive director of the Future of.
Speaker 3: Life Institute, joining us on site. Thank you so much
Speaker 3: for coming by with us. We are trying to figure
Speaker 3: out technology AI, what it means for our workplace, for
Speaker 3: our life in general.
Speaker 4: What are some of the biggest the biggest facets of
Speaker 4: that discussion or narrative that kind of occupy your mind today.
Speaker 12: I think there are some major challenges that we have
Speaker 12: that AI is presenting us with. One is the issue
Speaker 12: of how are we going to make AI in a
Speaker 12: way that is actually safe and beneficial for society. Right now,
Speaker 12: we have AI systems that are being developed by sort
Speaker 12: of a handful of very large companies, and they're doing
Speaker 12: it in a very competitive way. So each of those
Speaker 12: companies feels like it has to develop the new, better
Speaker 12: system faster than its rivals. Does we even see this
Speaker 12: on the international stage where that you know, the US
Speaker 12: has rhetoric like we have to develop AI faster than
Speaker 12: our geopolitical rivals.
Speaker 9: And this is not the way.
Speaker 12: It's a race, and a race is not the way
Speaker 12: you get something to go as safely as possible.
Speaker 3: Right.
Speaker 12: The race is the way that you get things to
Speaker 12: go as quickly as possible, and speed does not necessarily
Speaker 12: equal safety. So I think one of the problems that
Speaker 12: you know, we have to step out of this dynamic
Speaker 12: of there's a competitive race to develop more and more
Speaker 12: powerful systems, even at the expense of making sure that
Speaker 12: those systems are safe and beneficial systems for society.
Speaker 9: So that's issue one.
Speaker 2: I say, what's at stake here? If those guardrails aren't
Speaker 2: in place? I think, like, what's worst case scenario? The
Speaker 2: get give it to us full.
Speaker 12: I think they're short term scenarios that we see that
Speaker 12: are that are worries and long term one. So I
Speaker 12: think in the short term, we see that our whole
Speaker 12: sort of information gathering and understanding and dissemination system are
Speaker 12: the ecosphere is more or less being dismantled. You know,
Speaker 12: right now we are becoming a wash in AI generated content.
Speaker 12: You don't really know most of the things that you read,
Speaker 12: whether they AI generated or human generated.
Speaker 6: It.
Speaker 12: We will soon be at the point where the pictures
Speaker 12: that you see are more or less indistributable between AI
Speaker 12: generated and camera generated. That's already sort of possible. So
Speaker 12: we have a kind of pollution of our information commons
Speaker 12: to the extent that I think we're losing track of
Speaker 12: just what is real, what is human, what is true
Speaker 12: from what isn't. And so I think that's a challenge
Speaker 12: we're going to see play out in huge that's happening.
Speaker 9: That's happening now.
Speaker 2: I think that's not the robots taking over, that's that's.
Speaker 12: Right it's not the robots taking over, but it also isn't.
Speaker 12: It's also not not the robots taking over in the
Speaker 12: sense that we are replacing human generated culture and content
Speaker 12: with AI generated culture and content.
Speaker 4: How do you police that? How do you create the
Speaker 4: guardrails around that?
Speaker 12: I think there it's a So in terms of the
Speaker 12: content generation, it's a question of having ways to verify
Speaker 12: that something is authentic, that is real, that is true,
Speaker 12: that is human generated ways to detect and ways to
Speaker 12: label things that aren't, and having the technical systems that
Speaker 12: allow people to access that information. So it should be
Speaker 12: the case that if I go online and read a
Speaker 12: news article, I should know whether it's AI written or not.
Speaker 12: I should know whether a fact and it is true,
Speaker 12: and if it's claimed to be true, how do I.
Speaker 9: Know that it's true? I should be able to go
Speaker 9: back to like the camera they took that picture?
Speaker 3: How do you do that?
Speaker 12: Well, it's all possible technically, I mean the social systems
Speaker 12: and the like, and the the rules and the market
Speaker 12: demand to bring those things into the way we.
Speaker 2: Actually need use Berg as this article was written in
Speaker 2: the system of Bloomberg automation. I mean, not everybody does that, though,
Speaker 2: I guess right.
Speaker 12: So, so should there be a rule a law, of course,
Speaker 12: I mean there should certainly be certain rules about fake information,
Speaker 12: so it should. I think it should not be legal
Speaker 12: to generate non consensual deep fakes of people that they
Speaker 12: didn't authorize, whether they're sexual deep fakes or political deep
Speaker 12: fakes that are or fraudulent business you know deep talking
Speaker 12: to politicians.
Speaker 2: Right now to make this reality we are.
Speaker 6: Yeah.
Speaker 12: So there are lots of bills in Congress that are
Speaker 12: pursuing the deep fakes issue. I think some of them
Speaker 12: are underpowered in the sense that they predominantly put the
Speaker 12: put the onus on content creators not to create deep fakes,
Speaker 12: but they don't put the onus on developers not to
Speaker 12: create the tools for deep fakes, and not necessarily enough
Speaker 12: on platforms to make sure that they label things correctly.
Speaker 9: So I think we need lots of things there.
Speaker 12: Some of those will happen by themselves because the market
Speaker 12: will require some of them will be required.
Speaker 9: We will need regulations in law scot I'm.
Speaker 3: Just kind of a little terrified thinking about social media.
Speaker 3: I the amount of news information that's not accurate that's
Speaker 3: already out there, and we've not done a great job
Speaker 3: policing that.
Speaker 4: So I'm my favors crossing everything.
Speaker 9: You need to do a little better this time, you
Speaker 9: need to do a little better.
Speaker 4: We've learned.
Speaker 2: We'll see. We'll check in with you in a little
Speaker 2: while and see if we've done a better job.
Speaker 9: But the broader question, so you asked about the long
Speaker 9: term and the short.
Speaker 2: Term, so we'll see, Well, we'll see if it We'll
Speaker 2: see if we can if we can pull it off.
Speaker 2: All right, Anthony, thank you so much for joining us.
Speaker 2: That's Anthony Gary, executive director of the Future of Light
Speaker 2: and Light Institute, here at the Bloomberg Tech Summit.
Speaker 1: You're listening to the Bloomberg Business Week podcast. Catch us
Speaker 1: Live weekday afternoons from two to five pm Eastern Listen
Speaker 1: on Apple card Play and then brought auto with a
Speaker 1: Bloomberg Business at or want us live on YouTube.
Speaker 2: Well, our next guest needs going to We're going to
Speaker 2: get them one anyway. It's a Silicon value vis He
Speaker 2: helped build PayPal, co fided LinkedIn. He was an early
Speaker 2: investor in Facebook and Airbnb. He was the first investor
Speaker 2: in open Ai. He co founded the ai company in
Speaker 2: Flection Ai. He's on Microsoft Forard. He's a partner at
Speaker 2: the VC firm Braylock Partners. He's a New York Times
Speaker 2: bestselling author, and he's also a podcast we have read
Speaker 2: hot mon.
Speaker 7: Great to be here, Thank you for you.
Speaker 10: As we were just talking how does the environment? But
Speaker 10: we've ever done a radio show before it so hopefully
Speaker 10: it'll work.
Speaker 9: It's working so far, so far, so good.
Speaker 2: But I have to ask you, are you real or
Speaker 2: am I talking to some sort of AI digital twin
Speaker 2: rand Well, and explain why I have to ask that question.
Speaker 10: So as you as you know, I did an interview
Speaker 10: with myself where I was talking to my own digital
Speaker 10: twin read AI, and I did it in order to
Speaker 10: kind of show that not only obviously there's a whole
Speaker 10: bunch of concerns.
Speaker 7: There's concerns and political.
Speaker 10: And misinformation and a deep makes and a bunch of
Speaker 10: other stuff that are real con but even here there's
Speaker 10: optimism to look at what's to be shaped towards. And
Speaker 10: I wanted to show not just hell, that message. And
Speaker 10: so I was like, okay, well let me talk to
Speaker 10: my own three day I and see how it works.
Speaker 10: And so and the reason why you asked that question
Speaker 10: of course, because you said, well, wait a minute, that
Speaker 10: was pretty good.
Speaker 7: It was we're here in person. You can tell this
Speaker 7: is I'm the real name.
Speaker 2: That sounds like this looked like you, Yes, yeah, this
Speaker 2: is like it looked like talking.
Speaker 7: To a video audio and the words we're all AI
Speaker 7: generated zero from me. It was other than mirroring off
Speaker 7: my earlier videos.
Speaker 2: Mirroring off my earlier podcast, use your your use your
Speaker 2: book to train as well.
Speaker 10: Yes, okay, yeah, it used all everything ever did answers
Speaker 10: the way read would get answers.
Speaker 3: We're all gonna have digital twins someday and we're gonna
Speaker 3: hear it was and we're like, go.
Speaker 2: To the d m V for me.
Speaker 7: So I think we must. It's certainly possible.
Speaker 10: Certainly, if you're a media person you'll have a digital twin. Certainly,
Speaker 10: if you're a leader, you'll have a digital twin.
Speaker 7: It'll be used in a front.
Speaker 10: If you're a lawyer, you'll have one because then people
Speaker 10: can talk to your digital twins and maybe at a
Speaker 10: cheaper rate.
Speaker 7: The dog you are prepping for your meeting or that
Speaker 7: kind of thing.
Speaker 10: So I think it will be a stack of harriers
Speaker 10: for digital twins will be very real.
Speaker 7: But I'm not sure all eight billion people in the
Speaker 7: world will.
Speaker 2: This string well, so why should this excite us and
Speaker 2: not scare us and want us to all move to bunkers.
Speaker 10: So it should look naturally, it should both excite and
Speaker 10: scare us. The scars is, the negatives is the scarris
Speaker 10: is of political misinformation. You know, things that are going
Speaker 10: to be happening this year in the US until we're
Speaker 10: in other major elections of democracy. It should scare us
Speaker 10: because there's questions around them. And let if someone created
Speaker 10: a deep make of me doing something or saying something
Speaker 10: I really am like you know, like you know that
Speaker 10: I think Trump is a corruption in democracy against the
Speaker 10: rule on what happens to you. I love Trump, you know,
Speaker 10: that would be obviously a problem. And so there's all
Speaker 10: kinds of ways that there are real problems. So on
Speaker 10: the other hand, we will we will, as we always
Speaker 10: do with technology to figure out how to navigation, will
Speaker 10: get that not perfectly, but sufficiently, and there will be
Speaker 10: great things like for example, that's part of the reason
Speaker 10: I started showing, Hey.
Speaker 7: Look here, I'm making a deep bag of myself and
Speaker 7: it's not that bad.
Speaker 4: You know, read when you sat down I said, the conversations.
Speaker 3: We have a lot of Bloemberg and we've written about
Speaker 3: this is here.
Speaker 4: You have Lincoln kind of the social media site, that
Speaker 4: kind of the social media site.
Speaker 3: That seems to be clean, pure, You can truss and
Speaker 3: you can have conversations, so we can get it right.
Speaker 4: So what how is that kind of a guide in
Speaker 4: yours since in terms of jen ai, and how do
Speaker 4: you think about and what are the guard rails? How
Speaker 4: do we regulate it?
Speaker 10: Yes, and so the good news is the mostly frontier
Speaker 10: model companies, Microsoft, open Ai, Google are all putting a
Speaker 10: lot of energy in that.
Speaker 7: They're making these models healthy.
Speaker 10: Participants within the US, within the global kind of media ecosystem,
Speaker 10: like don't generate fake information, be.
Speaker 7: Civil, you don't do hate speech, don't enab it self harm.
Speaker 7: They all put a lot of energy and a lot
Speaker 7: of work in that. And I don't invest hundreds of
Speaker 7: millions of dollars and teams of hundreds of people in
Speaker 7: order to do that.
Speaker 10: Now, one of the challenges is is that some of
Speaker 10: these models are open source, and as an open source,
Speaker 10: someone else takes the open source model to.
Speaker 7: Something that's not any of that. With that right and
Speaker 7: that's part of the reason why we still have to
Speaker 7: navigate this.
Speaker 3: Do you have trust so that we can navigate it
Speaker 3: correctly and safely in the future AI, So.
Speaker 7: The ultimate answer is absolutely yes.
Speaker 10: That doesn't mean that there aren't potholes, you know, bumps
Speaker 10: in the road, thunder scrapes, all the rest, and it's
Speaker 10: I guarantee you there will be those two.
Speaker 2: The US can't get Vladimir Putin not to invade in Ukraine.
Speaker 2: The world can't get him not sure stop fighting. What
Speaker 2: convinces you that we could get a leader like him
Speaker 2: not to use AI?
Speaker 7: Oh bad? Zero percent?
Speaker 10: Like if you said that that Putin will be using
Speaker 10: AI to disrupt the US elections, you know, probably support
Speaker 10: Trump because that's his exit strategy from Ukraine. Uh, he
Speaker 10: will do that one hundred percent. Is no way it's
Speaker 10: having it. The defense is not getting him not to
Speaker 10: do it. The defense is integrating AI in our own
Speaker 10: tech platforms and using our stronger AI in defense.
Speaker 2: So essentially saying, okay, well, maybe you see something on
Speaker 2: Facebook and that platforms might have developed something that's okay,
Speaker 2: Well this isn't necessarily something that's true, Yes, but do
Speaker 2: you trust Do you trust Facebook?
Speaker 12: To do that.
Speaker 7: Actually, I.
Speaker 2: Yes, And you have a deep history with the company.
Speaker 7: Yes, I have a deep history of the company.
Speaker 10: I actually have talked to Zuckerbiger about it, and they're
Speaker 10: investing in it. I think they're making a real effort
Speaker 10: at it, so I think like they're really trying. I'm
Speaker 10: more worried about Twitter that I am about Facebook on
Speaker 10: this matter.
Speaker 2: Okay, why are you more worried about Twitter?
Speaker 10: Well, because look someone you also go way yeah, and look,
Speaker 10: Elon is A is literally one of the heroes of
Speaker 10: our generation. You know, uh, Space and I think and
Speaker 10: kind of Starlink and Tesla and Evie.
Speaker 7: Just amazing, amazing, amazing. We wouldn't have any of this
Speaker 7: about him. It is so spectacular.
Speaker 10: On the other hand, before he buys Twitter, he's like, oh,
Speaker 10: we have this problem with robots. And then after he
Speaker 10: bought trying to get out of the and then after
Speaker 10: you buy what robots and you're like, well, the robots
Speaker 10: are still there. There's still like Internet Research Agency watching
Speaker 10: robot farms doing shit.
Speaker 7: Are you doing anything about them?
Speaker 2: I'm not hearing anything, to be fair, I did see
Speaker 2: I did see an ad on Twitter recently with a
Speaker 2: deep bake of Jeff Bezos pushing a cryptocurrency. Yeah, it's
Speaker 2: a paid ad. Yes that has showed up repeatedly in
Speaker 2: my feed obviously not approved vice.
Speaker 7: Yes, yes, yeah, and so therefore, what are you doing
Speaker 7: about AI and JEMA?
Speaker 4: Well, you know, Elon is so complex.
Speaker 3: Back from Milton, he did a conversation with Michael Milton.
Speaker 3: He said, very important to have maximum seeking AI and
Speaker 3: maximum curious.
Speaker 4: AI, and then it's tied not to lie or do
Speaker 4: things that are not true.
Speaker 7: Well, walk the lock, don't just talk the talk, well.
Speaker 3: Said, can I ask, I'm curious if we have all
Speaker 3: these conversations about jen Ai, how is it going to
Speaker 3: impact my life? How is it really going to impact
Speaker 3: him's life? How's it really going to impact your life?
Speaker 7: So here's a simple way of looking at all of
Speaker 7: us are going to have as an all AI assistant
Speaker 7: that it is going to be helping us with its
Speaker 7: focus on us. Right, so it'll be like, hey, what
Speaker 7: do you need help with? Do you need help with
Speaker 7: figuring out say something like like where to go? What's
Speaker 7: entertaining to do? You know in the city?
Speaker 10: And I or oh I'm having this different I'm trying
Speaker 10: to figure out this thing with my kids. Oh, we
Speaker 10: can help you with that. Oh, I'm trying to figure
Speaker 10: this medical thing. Oh I can help you with that. Oh,
Speaker 10: I'm trying to figure out I had this difficult conversation
Speaker 10: with coworker.
Speaker 7: Oh, I'll talk to you about that. It will help
Speaker 7: us with a whole range of things. And like, for example,
Speaker 7: part of what we found.
Speaker 10: An inflection was really surprising to us and very positive.
Speaker 10: Which has podge in personal intelligence is people.
Speaker 7: Will say, oh, I got these eight ingredients in my friends,
Speaker 7: what should I name?
Speaker 10: Or oh, my toaster broke and I fixed it, and
Speaker 10: you're like, actually, in fact, it helps all of that.
Speaker 10: So that's the exact human amplification that helping us navigate
Speaker 10: our lives, which is the thing I guarantee will be there.
Speaker 2: I love the ingredients in the fridge of it. If
Speaker 2: you're just joining us, we're speaking to with Rida Hoffman,
Speaker 2: the PayPal of LinkedIn, Open Ai, of Inflection AI, of
Speaker 2: the podcast Possible. But this certainly goes on read I'm
Speaker 2: wondering about winners and losers when it comes to AI AI.
Speaker 2: In terms of companies. You're on the board of Microsoft Imagined,
Speaker 2: A couple of the big companies that you've invested in,
Speaker 2: that you've founded. Is there a concern that we're just
Speaker 2: going to see the big companies like Microsoft, like in video,
Speaker 2: like Amazon, like meta platforms, they're going to be the
Speaker 2: only winners when it comes to AI.
Speaker 7: What I guarantee you They're not going to be the
Speaker 7: only one. They will be winners.
Speaker 6: Right.
Speaker 10: Satia has just done a masterful job, like like remember
Speaker 10: it started with a million dollars deal with a five
Speaker 10: O WEBC three. I think in the first time in
Speaker 10: the history something like that's happening, like genius strategy from
Speaker 10: talking and I think it will be Uh, it'll across
Speaker 10: all of these companies. I think they will have wrong
Speaker 10: winds going into the future. On the other hands, you know,
Speaker 10: at Gray Locke, we're investing a whole bunch of AI company.
Speaker 10: We do it reasonably well.
Speaker 7: We have a whole portfolio that we're excited about. And
Speaker 7: I think that the I think that it's just you
Speaker 7: don't play the same game. It's a little bit like
Speaker 7: and you said.
Speaker 10: Hey, I got a start up, I'm gonna try to
Speaker 10: make a new desktop search company.
Speaker 7: You're like, well, one of the difficults, right there is
Speaker 7: this company called Google.
Speaker 10: It's a little challenging. Okay, you know I'm gonna make
Speaker 10: a new handset mobile phone devices. You're like, oh, there's
Speaker 10: this company called that whole it's.
Speaker 7: A little challenging, so you know, you don't do it
Speaker 7: that way. But there's gonna be a whole range of
Speaker 7: other AI companies the things that will like.
Speaker 10: Everything from opportunities that the large tech companies just can't
Speaker 10: focus on.
Speaker 7: To taking interesting risks and making that risk look good
Speaker 7: and then all of a sudden building out ding. So
Speaker 7: I think there's gonna be a range of startups. Don't
Speaker 7: look excited the lights podcasts.
Speaker 4: We have a great podcast. You have a great new podcast.
Speaker 4: Tell us about possible, U tell us about it? Like,
Speaker 4: really want to talk too?
Speaker 7: What are the conversations you want to have? So for me,
Speaker 7: it's possible.
Speaker 10: It's too much of the dialogue is about technology being
Speaker 10: dangerous to us, how we evolve this.
Speaker 7: Humanity, how we become better and more human. It's food, technology,
Speaker 7: it's it's clothing, it's.
Speaker 10: Glasses, it's it's my it's food, it's cooking, it's fired,
Speaker 10: it's buildings.
Speaker 7: All of this is.
Speaker 10: Technology that's helped us make us as the human games
Speaker 10: we are AI will be saying, because.
Speaker 7: The whole point I'm on the Possible podcast used to say,
Speaker 7: this is how technology can help.
Speaker 10: Us become more human, not to go, oh my god,
Speaker 10: what's coming in technology. It's it can be great for us,
Speaker 10: and it's not that hard to shape. We just need
Speaker 10: to shape it, whether it's AI, whether it's the use
Speaker 10: of phones. And you know, obviously people like to talk
Speaker 10: about what social networks and they go, wow, that's been
Speaker 10: to have a challenging It's like, well, look at LinkedIn.
Speaker 10: LinkedIn's worked out pretty well. It's doable. It's doable, so
Speaker 10: let's do it.
Speaker 2: We don't want to end with something that everybody loves
Speaker 2: to talk about. Politics.
Speaker 4: We all agree.
Speaker 2: Look, you've been open about your feelings about Dwain Trump.
Speaker 2: You help fund e Gene Carroll's defamation lawsuits against the
Speaker 2: former president. There are a lot of business leaders out there,
Speaker 2: some of them people you work with very closely, to
Speaker 2: say that business under a President Trump administration was better
Speaker 2: than business under a Biden administration. And that's why we're
Speaker 2: in the corner of Donald Trump. When it comes to
Speaker 2: twenty twenty four, What do you say to them?
Speaker 10: So I understand the approach that Trump reason is more
Speaker 10: regulatory lightweight than Biden. And by the way, generally speaking,
Speaker 10: being more regulatory lightweight is a good thing. I try
Speaker 10: to encourage the Biden administration to do that. On the
Speaker 10: other hand, what's more fundamental is the rule of law.
Speaker 10: Business works much much better with a healthy, strong rule
Speaker 10: of law.
Speaker 7: We do not want to have leaders who are literally
Speaker 7: in a court like have.
Speaker 10: Been convicted by court of you were slandering about your
Speaker 10: sexual assault and a jury found you guilty. Right, we
Speaker 10: should be a rule of law country first. And by
Speaker 10: the way, this is what's the business leaders. By the way,
Speaker 10: rule of law is what makes great business.
Speaker 7: That's the reason why.
Speaker 10: Actually Biden is a matter of president for business. Even
Speaker 10: though the regulatory thing won't be exactly what.
Speaker 7: You want and we'll have to work on it. But
Speaker 7: rule of laws.
Speaker 4: Fundamental in your perspective, your point of view.
Speaker 7: Yes, I'm not yes, this is, but I do wonder.
Speaker 3: That you know soon as you look at the November
Speaker 3: election that outcome if it is not another of Biden
Speaker 3: White House present a Trump former presidents come back in
Speaker 3: the White House, what does.
Speaker 4: It mean for the tech industry or your or your
Speaker 4: group in terms of the rule of law is not followed.
Speaker 10: Well, so look, I think it's the tech industry can
Speaker 10: tribe under either administration.
Speaker 7: But I do think that if.
Speaker 10: Either Biden or Trump. But if I think Trump's elected,
Speaker 10: I think history will look back as the beginning of
Speaker 10: the end of the American world order, and that will
Speaker 10: have a massive effect on global business.
Speaker 2: How far are you willing to go to to reelect
Speaker 2: your bodies.
Speaker 10: Well, I'm willing to invest, I'm willing to speak, I'm
Speaker 10: willing to campaign, I'm willing to try to. Like when
Speaker 10: a prominent business leader speaks up and says I'm pro drop,
Speaker 10: I call them and I.
Speaker 7: Said, let's talk about it.
Speaker 9: Do you ever change their mind?
Speaker 7: Of course? Look for example, Look, one of things you
Speaker 7: have to do is think about blind spots.
Speaker 10: Like I just said something that was positive about how
Speaker 10: Trump's administration was running.
Speaker 7: Like I inspite to say you want a new regulation,
Speaker 7: we're moving old one. It's an exactly right thing.
Speaker 4: But I think what you.
Speaker 3: Said about globally the perception of the rest of the
Speaker 3: world potentially what the US means and what it is
Speaker 3: in terms of.
Speaker 4: That's a bigger story.
Speaker 10: People will not trust us live. They will say, now
Speaker 10: no longer trust that. You're into the world of law,
Speaker 10: an equal system, all the rest.
Speaker 3: All right, if you weren't in a world where Jennai
Speaker 3: was everything twenty seconds.
Speaker 4: What's the other technology we should have it on?
Speaker 10: Radars don't work and career well, so the other thing
Speaker 10: that's fallen behind it is synthetic biology. And when you
Speaker 10: put them together, by the way, like the invention of
Speaker 10: new pharmaceuticals, new medicines, everything else, it's like, let's just
Speaker 10: hold on to get to the future, because the future
Speaker 10: can be so amazing.
Speaker 4: Do you think about what a I could do? Right,
Speaker 4: it's just play around. Thank you so much, Thank you
Speaker 4: for enduring my pleasure. Appreciate it. Read, Thank you so much.
Speaker 9: That's read.
Speaker 2: Hoffman of Paypo linked New York Times best selling author
Speaker 2: his podcasts The Possible Podcast Season two started. It's out
Speaker 2: No love is.
Speaker 4: Love It all right, folks who are listening, row to
Speaker 4: Bloomberg Business Week.
Speaker 3: We're live at the Bloomberg Technology Summer in San Francisco.
Speaker 1: This is the Bloomberg Business Week podcast, available on Apple, Spotify,
Speaker 1: and anywhere else you get your podcast. Listen live weekday
Speaker 1: afternoons from two to five pm Eastern, on Bloomberg dot Com,
Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business. You
Speaker 1: can also watch us live every weekday on YouTube and
Speaker 1: always on the Bloomberg terminal.